In obstacle detection systems based on online vision, an essential preprocessing step for the obstacle classification consists of a detection of image regions which is efficient with respect to the computing time, with it being assumed of such image regions that they contain the obstacles of interest, whereby the computing effort is reduced overall and more robust real time classification software is made possible.
The obstacle detection with reference to a single gray scale image is of advantage to the extent that it enables an efficient calculation and is independent of the inherent movement of the vehicle having the detection system, of changes in light intensity, etc.
Various applications exist in which one-dimensional or two-dimensional profiles are produced for the obstacle detection. These applications are either monitoring systems or obstacle detection systems with infrared sensors in which the contour of the obstacles can be unambiguously detected either by a background subtraction or by the sensor. The one-dimensional or two-dimensional profiles of these applications can unambiguously describe the obstacles detected. In contrast, a direct one-dimensional or two-dimensional profile does not work in a gray scale image due to the complexity of the image scene and the variety of the pixel intensities.